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...r [36] studied what aggregation functions may be more resilient against malicious attacks. Jadia and Mathuria [23] extend the approach of Hu and Evans by incorporating privacy. Mahimkar and Rappaport =-=[29]-=- also propose an aggregation-verification scheme for the single-aggregator model using a secret-sharing scheme. Du et al. [13] propose using multiple witness nodes as additional aggregators to verify ...

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...ise key distribution: In [2], a symmetric key can be generated among t nodes by evaluating a symmetric multivariate polynomial P (x1, ..., xt) at each node. Asymmetric group-wise key distribution: In =-=[18]-=-, the memory of each sensor node is pre-loaded with the ECC (elliptic curve cryptography) domain parameters. After deployment, each sensor will compute its EC-public/private key pair and broadcast its...

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... as well as the aggregated result to the base station. Since the aggregator point is fixed and responsible to handle so much traffic, the aggregator resources will not last long. Moreover, SecureDAV (=-=Mahimkar & Rappaport 2004-=-) improved the data integrity vulnerability in SDA and ESA by signing the aggregated data. In SecureDAV, each sensor within a cluster will have its share of its secret cluster key and then it will be ...

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...much more serious since even a single malicious sensor can completely corrupt the final result. Thus the need to make aggregation queries secure against the second attack has been widely acknowledged =-=[1, 2, 6, 10, 14, 15, 17, 25, 26]-=-. Previous results and motivation. Most pioneering efforts [1, 6, 14, 15, 17] on secure aggregation queries make strong restrictive assumptions (e.g., assuming a single malicious sensor [14, 15] or as...

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... where aggregation result is destined. In this paper, we only consider a single base station case. iPDA is readily extensible to multiple base station cases. In general data aggregation protocols [1] =-=[5]-=- [6], aggregation trees root at the base station are usually constructed. The non-leaf nodes, except the root, in the aggregation tree serve as intermediate aggregators. They are responsible for forwa...

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...in the presence of single [27, 31] or multiple [8, 47] adversarial sensor nodes. Also, different models of in-network data aggregation have been considered, including the star-based aggregation model =-=[14, 39, 47]-=- and the tree-based aggregation model [8, 61]. Aggregation of encrypted data is studied in [5, 7, 21]. 10sUnfortunately, these solutions are not feasible for mobile sensor networks. First, previous au...

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...rotocols do also not tolerate any failure, only recent proposals of Haghani et al. [23] and Taban et al. [38] bring in capabilities to detect malicious nodes as a way to provide robustness. SecureDAV =-=[28]-=- uses threshold public key cryptography, which we argue to be not suitable in a sensor network. Another way, that is followed by FAIR, is to base the integrity on witness nodes [16]. Robustness can be...

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...oach is that it can cause network congestion [3] and as a consequence some information may get lost. To avoid network congestion one solution consists in using proper in-network algorithms (e.g., see =-=[4, 5, 6, 7]-=-) that can reduce significantly the number of bytes exchanged across the WSN by aggregating data [8, 9, 10]. In fact, in many situations, what is needed are aggregated measures, such as the average te...

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...schemes raise power consumption concerns, since computation requirements for public key encryption is still considered high for WSNs [12]. Many hop-by-hop aggregation protocols in WSNs like [3], [6], =-=[9]-=-, [13], [17], provide more efficient aggregation operations and highly consider data integrity. However, since sensed data being passed to non-leaf aggregators are revealed for the sake of middle-way ...